| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869 | local __FILE__ = (function() return string.gsub(debug.getinfo(2, 'S').source, "^@", "") end)()package.path = path.join(path.dirname(__FILE__), "..", "lib", "?.lua;") .. package.pathrequire 'w2nn'torch.setdefaulttensortype("torch.FloatTensor")-- ref: https://github.com/torch/nn/issues/112#issuecomment-64427049local function zeroDataSize(data)   if type(data) == 'table' then      for i = 1, #data do	 data[i] = zeroDataSize(data[i])      end   elseif type(data) == 'userdata' then      data = torch.Tensor():typeAs(data)   end   return dataend-- Resize the output, gradInput, etc temporary tensors to zero (so that the-- on disk size is smaller)local function cleanupModel(node)   if node.output ~= nil then      node.output = zeroDataSize(node.output)   end   if node.gradInput ~= nil then      node.gradInput = zeroDataSize(node.gradInput)   end   if node.finput ~= nil then      node.finput = zeroDataSize(node.finput)   end   if tostring(node) == "nn.LeakyReLU" or tostring(node) == "w2nn.LeakyReLU" then      if node.negative ~= nil then	 node.negative = zeroDataSize(node.negative)      end   end   if tostring(node) == "nn.Dropout" then      if node.noise ~= nil then	 node.noise = zeroDataSize(node.noise)      end   end   -- Recurse on nodes with 'modules'   if (node.modules ~= nil) then     if (type(node.modules) == 'table') then	for i = 1, #node.modules do	   local child = node.modules[i]	   cleanupModel(child)	end     end   end      collectgarbage()endlocal cmd = torch.CmdLine()cmd:text()cmd:text("cleanup model")cmd:text("Options:")cmd:option("-model", "./model.t7", 'path of model file')cmd:option("-iformat", "binary", 'input format')cmd:option("-oformat", "binary", 'output format')local opt = cmd:parse(arg)local model = torch.load(opt.model, opt.iformat)if model then   cleanupModel(model)   torch.save(opt.model, model, opt.oformat)else   error("model not found")end
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